Plotly_hw05_JasmineLib

Self-contained code chunk for plotly graphic marking: - made a self-contained code chunk according to instructions provided by teaching team in an internal issue discussion

suppressPackageStartupMessages(library(gapminder))
suppressPackageStartupMessages(library(tidyverse))
suppressPackageStartupMessages(library(plotly))
suppressPackageStartupMessages(library(viridis))
suppressPackageStartupMessages(library(scales))
suppressPackageStartupMessages(library(RColorBrewer))

oil_consumption = read_csv(file ="Oil_Consumption_per_capita.csv")

## Parsed with column specification:
## cols(
##   .default = col_double(),
##   `Oil Consumption per capita (tonnes per year)` = col_character()
## )

## See spec(...) for full column specifications.

oil_consumption_2007 = oil_consumption %>% 
  select(`Oil Consumption per capita (tonnes per year)`, "2007") %>% 
  mutate(country = `Oil Consumption per capita (tonnes per year)`, 
         tonnes_per_capita_2007 = `2007`) %>% 
  select(country, tonnes_per_capita_2007)

gapminder_2007 = gapminder %>% 
  filter (year == "2007") %>% 
  select(country = "country", pop, gdpPercap, continent, lifeExp) 

gapminder_oil_2007 = left_join(gapminder_2007, oil_consumption_2007, by= "country") %>% 
  na.omit() 

## Warning: Column `country` joining factor and character vector, coercing
## into character vector

plot_oilvsgdp = gapminder_oil_2007 %>% 
  ggplot(aes(gdpPercap, tonnes_per_capita_2007)) + 
  geom_point(aes(colour = pop)) +
  scale_x_log10(labels = dollar_format())+
  scale_colour_distiller(
    trans="log10",
    breaks = 10^(0:9),
    labels = comma_format(),
    palette = "YlOrRd"
  ) +
  scale_y_continuous(breaks = c(0,2,4,6,8,10))+
  theme_bw()+
  ggtitle("Tonnes of Oil per Capita by GDP per Capita ")

ggplotly(plot_oilvsgdp)